In this HCI Webinar, Dr. Jonathan H. Westover talks with Sarah Smart and Sofia Whelan about how AI and automation are reshaping the way companies think about talent. Sarah Smart has over 20 years of leadership experience in Talent Acquisition at companies like Hilton Worldwide, Accenture, and JPMorgan Chase. During her career, Sarah has led global teams in the adoption of Generative AI-enabled technologies, new HCMS, and new processes that transform and align organizations to the new expectations in HR. In her most recent role, Sarah led the Product Organization for Talent Acquisition at JPMorgan Chase as well as leading the Chase Recruiting Organization. Sarah is also a founding member of the Human Centric AI Council, launched in 2025, shaping what human-centric AI looks like in HR. Sofia Whelan brings over 16 years of global HR transformation experience. She has a strong passion and deep focus on translating HR trends into programs that drive business value. During her time at Deloitte as a Human Capital consultant, she excelled at providing advice and implementation services related to HR Technology Strategy, Operating Models/ Org Design and Vendor Selections, as well as Transformation Execution and Change Management for a wide range of companies, including Google, Disney, Ab- Inbev, Pfizer and more. Prior to starting HorizonHuman Sofia led the design and delivery of a Product Operating Model and Skills Strategy at JPMorgan Chase.

This video explores the evolving role and capabilities of artificial intelligence (AI) in real-world tasks, moving beyond traditional academic-style testing. Historically, AI performance was measured by benchmarks akin to exams, assessing memory or problem-solving in controlled settings. However, real-life work is complex, unpredictable, and demands skills like common sense, creativity, empathy, and nuanced judgment. To address this gap, OpenAI developed the GDP val benchmark, which evaluates AI on hundreds of practical tasks across various professions, emphasizing economic value and real job performance rather than theoretical accuracy. Highlights 🤖 AI is moving beyond academic-style tests to practical, real-world job challenges. 🚀 OpenAI’s GDP val benchmark measures AI performance on tasks that drive the economy. ⚖️ AI matches or exceeds human experts in about half of evaluated professional tasks. 🧠 AI excels at processing large volumes of data and spotting patterns but lacks nuance and empathy. 🤝 The future of work is a human-AI partnership, combining speed and creativity. 🎨 Examples include AI-assisted design and medical research, with humans retaining final decisions. 📚 Training and ethical oversight are key to effectively integrating AI in workplaces. Key Insights 🤖 AI’s Real-World Testing Overcomes Traditional Limitations: Traditional AI benchmarks focused on academic-style assessments that measured memory or problem-solving in isolation, which do not capture the messy, complex nature of real-world jobs. GDP val’s approach to testing AI on actual professional tasks provides a more meaningful measure of AI’s practical utility and limitations, reflecting economic impact rather than theoretical ability. This shift is crucial for understanding where AI can genuinely add value in workplaces. ⚙️ Versatility and Adaptability Highlight AI’s Strengths and Weaknesses: The GDP val benchmark tests AI across hundreds of tasks spanning numerous professions, emphasizing adaptability to different rules and contexts. AI’s performance at about 50% parity with human experts shows strong versatility but also underlines that half the time, AI lacks the necessary insight or flexibility to replace humans. This nuanced understanding helps businesses identify where AI can automate efficiently and where human skills remain indispensable. 📊 AI Excels in Data-Intensive, Pattern Recognition Tasks: AI’s superhuman ability to process massive datasets quickly and detect patterns makes it invaluable in fields like legal document analysis, financial report evaluation, and programming at certain levels. These strengths can dramatically reduce repetitive workloads and improve accuracy in routine or volume-heavy processes, demonstrating AI’s potential as a productivity multiplier rather than a standalone decision-maker. 💡 Human Judgment, Creativity, and Empathy Remain Irreplaceable: Despite AI’s advances, tasks requiring genuine creativity, strategic thinking, and emotional intelligence are still firmly in the human domain. AI can generate alternatives or suggest possibilities but cannot replace the nuanced decision-making that considers community impact, ethics, or deep understanding. This reinforces the need for human oversight and the complementary “centaur” working model. 🤝 The Centaur Model as the Future of Human-AI Collaboration: The concept of blending AI’s computational power with human judgment offers a balanced, pragmatic path forward. AI acts as a co-pilot—handling grunt work and providing rapid analysis—while humans remain captains who steer decisions and adapt to unpredictable scenarios. This synergy promises enhanced innovation and efficiency without sacrificing ethical considerations or creativity. 🔄 Workflows and Training Must Evolve Alongside AI Integration: The video stresses that successful AI adoption requires redesigning workflows to incorporate AI as a collaborator, not a replacement. Investing in employee training to craft effective prompts, evaluate AI outputs critically, and know when to override AI decisions is essential. Organizations that prioritize this learning curve will be better positioned to harness AI’s benefits responsibly. 🛡️ Humans as Ethical Guardians and Innovators: AI systems can perpetuate biases and make confident but incorrect assertions, highlighting the importance of human oversight. Humans serve as ethical gatekeepers, ensuring AI outputs align with societal values and community needs. Furthermore, humans drive true innovation by integrating empathy and broader context—elements AI cannot replicate—thus securing a vital role in the AI-augmented future. #GDPval #AIbenchmark #HumanAICollab #AIEconomy OUTLINE: 00:00:00 - Right, let's talk about how clever these AI things really are 00:01:07 - A proper test for the digital brains (GDPval) 00:02:24 - So, how did the AI do? 00:03:33 - Humans and AI on the same crew 00:04:30 - What's next? Getting ready for the co-driver of the future

This video explores the common misconception among executives who believe they are strategic leaders when, in reality, many excel primarily as operational managers focused on short-term execution rather than long-term strategic thinking. True strategic leadership is a rare and complex skill that involves seeing the bigger picture—connecting an organization’s internal realities with external industry trends and global changes to create adaptable, forward-looking plans. Unlike operational management, which concentrates on maintaining current processes and performance, strategic leadership requires scanning the environment for future opportunities and threats, synthesizing diverse information, and making bold decisions under uncertainty. Highlights 🔍 Many executives confuse operational excellence with true strategic leadership. 🌍 Strategic thinking requires connecting internal realities with external trends and global changes. 🎯 Five pillars define strategic competency: understanding present, future planning, vision, communication, and disciplined execution. 🧠 Cognitive biases and lack of feedback often inflate leaders’ self-perceptions of strategic ability. 🛑 Strategy is frequently misused to describe operational initiatives, causing organizational drift. 📊 Data-driven 360 assessments reveal blind spots and guide targeted development. 🚀 Embedding strategic thinking into culture fuels innovation, resilience, and sustainable growth. Key Insights 🔎 Misconception of Strategic Leadership: Many executives equate their operational management skills—such as managing budgets, optimizing processes, and hitting quarterly targets—with strategic thinking. This conflation leads to a false sense of security about the future direction of their organizations. The insight here is that operational excellence, while critical, is fundamentally different from the mindset and skillset required to anticipate and shape long-term success. This distinction is vital for organizations to recognize if they want to avoid stagnation and vulnerability to disruption. 🌐 Holistic View is Crucial: True strategic leaders take a broad perspective that includes customers’ unmet needs, hidden competitors, market realities, and financial health. This comprehensive understanding forms the foundation for meaningful strategy. Leaders who focus solely on their numbers or internal performance metrics miss the dynamic context in which their organizations operate, limiting their ability to respond to change effectively. 🔮 Future Planning Requires Structured Foresight: Effective strategy involves looking far beyond immediate horizons—3, 5, or even 10 years ahead—using disciplined trend analysis in technology, economics, and society. This foresight is not guesswork but a systematic approach to envisioning plausible futures and preparing flexible roadmaps. Organizations that neglect long-term planning risk being blindsided by disruptive shifts and losing competitive advantage. 🎤 Communication and Influence Are Strategic Pillars: Strategy is not simply a plan on paper; it requires rallying the organization through storytelling, coalition-building, and stakeholder management. Leaders must be master communicators who can translate complex ideas into compelling narratives that inspire collective action. Without this skill, even the best strategies remain unused or poorly executed. 🔄 Execution with Adaptation is Key: Strategy is a continuous process, not a one-time event. Leaders must execute with discipline, create feedback loops, and be willing to pivot based on learning and changing conditions. Treating failure as a learning opportunity fosters resilience and agility, enabling organizations to navigate uncertainty more effectively. ⚠️ Cognitive Bias and Feedback Vacuums Undermine Strategic Development: The Dunning-Krueger effect causes many leaders to overestimate their strategic capabilities, while organizational dynamics often filter or mute honest feedback. This creates an echo chamber where inflated self-perceptions go unchallenged, perpetuating strategic weaknesses. Recognizing and addressing this psychological and cultural barrier is essential for genuine growth. 🌱 Culture and Continuous Practice Sustain Strategic Capability: Strategy cannot be a sporadic activity confined to senior leaders or annual retreats. Embedding strategic thinking into the organizational culture—through regular discussions, safe-to-fail pilot projects, and rewards for innovation—builds a shared capability that drives better decision-making at all levels. This cultural shift transforms strategy into a living, evolving discipline that enhances clarity, innovation, and competitive advantage over time. OUTLINE: 00:00:00 - The Grand Illusion of Strategy 00:01:11 - What Does It Mean to Be Strategic? 00:02:44 - The Five Pillars of True Strategic Leadership 00:03:55 - The Dangerous Gap Between Perception and Reality 00:05:10 - Building Bridges to Strategic Excellence

Abstract: This article examines OpenAI's recently released GDPval benchmark, which represents a significant advancement in evaluating artificial intelligence capabilities on economically valuable knowledge work. Unlike previous AI evaluations that focus on academic reasoning or specific domains, GDPval assesses performance on real-world tasks spanning 44 occupations across 9 major economic sectors that contribute $3 trillion annually to the U.S. economy. Analysis of benchmark results reveals that frontier AI models are approaching expert-level performance on many professional tasks, with the best models winning or tying with human experts approximately 50% of the time. The benchmark also demonstrates that human-AI collaboration strategies can potentially increase productivity while maintaining quality. This article synthesizes the methodology, findings, and implications of GDPval, offering evidence-based recommendations for organizations seeking to integrate AI capabilities into knowledge work processes. While these results show impressive AI progress on standalone professional tasks, they should be interpreted as indicators of task-level capabilities rather than predictions of occupational displacement.

Abstract: This article explores the prevalent discrepancy between perceived and actual strategic competencies among organizational leaders. Drawing on recent research in leadership development, cognitive biases, and organizational performance, the analysis reveals that many executives overestimate their strategic capabilities, creating significant performance gaps within organizations. The research examines five core strategic competencies: understanding present contexts, envisioning futures, influencing systems, delivering results, and adapting to change. The findings demonstrate that addressing these competency gaps through systematic assessment and targeted development can significantly improve organizational performance, strategic execution, and leadership effectiveness. The article presents evidence-based approaches to close these gaps, providing practical frameworks for organizations seeking to enhance their strategic capabilities in increasingly complex business environments.

In this podcast episode, Dr. Jonathan H. Westover talks with Sarah Smart and Sofia Whelan about how AI and automation are reshaping the way companies think about talent. Sarah Smart has over 20 years of leadership experience in Talent Acquisition at companies like Hilton Worldwide, Accenture, and JPMorgan Chase. During her career, Sarah has led global teams in the adoption of Generative AI-enabled technologies, new HCMS, and new processes that transform and align organizations to the new expectations in HR. In her most recent role, Sarah led the Product Organization for Talent Acquisition at JPMorgan Chase as well as leading the Chase Recruiting Organization. Sarah is also a founding member of the Human Centric AI Council, launched in 2025, shaping what human-centric AI looks like in HR. Sofia Whelan brings over 16 years of global HR transformation experience. She has a strong passion and deep focus on translating HR trends into programs that drive business value. During her time at Deloitte as a Human Capital consultant, she excelled at providing advice and implementation services related to HR Technology Strategy, Operating Models/ Org Design and Vendor Selections, as well as Transformation Execution and Change Management for a wide range of companies, including Google, Disney, Ab- Inbev, Pfizer and more. Prior to starting HorizonHuman Sofia led the design and delivery of a Product Operating Model and Skills Strategy at JPMorgan Chase.  Check out all of the podcasts in the HCI Podcast Network (https://www.podbean.com/podcast-network/HCI) !

In this HCI Webinar, Dr. Jonathan H. Westover talks with Jim Frawley about how executives and HR leaders can adapt to change. Jim Frawley is an expert in change management and organizational development, and the founder of the Bellwether Method. Jim is a renowned keynote speaker, the host of Jim's Take the podcast, a big-time reader, small-time triathlete, and full-time father and husband.

This video explores the transformative impact of artificial intelligence (AI) tools on human cognition and productivity. It begins with a vivid scenario illustrating how AI can rapidly complete complex tasks, such as summarizing data and drafting reports, which once took hours or days. This efficiency, however, comes at a cognitive cost. The video introduces the concept of cognitive offloading—the practice of using external tools to reduce mental effort—which has evolved from simple aids like writing or abacuses to sophisticated AI systems capable of reasoning, analysis, and creation. While AI can enhance productivity, it risks diminishing the brain’s intellectual engagement and neuroplasticity by encouraging passivity and reliance on algorithms. The brain, a dynamic organ that strengthens through use, may suffer atrophy in critical thinking, creativity, and memory if its “mental muscles” are not exercised. Highlights 🤖 AI can complete complex cognitive tasks in minutes, drastically improving productivity. 🧠 Cognitive offloading has evolved from simple tools to advanced AI that reasons and synthesizes information. ⚠️ Over-reliance on AI risks intellectual atrophy by reducing critical thinking and creativity. 🔄 The brain’s neuroplasticity requires active mental engagement to maintain and grow cognitive skills. 💡 Conscious, deliberate human-AI collaboration is essential to preserve intellectual rigor. 📅 Implementing habits like “AI Free Fridays” encourages critical thinking and mental exercise. 🌟 The future of AI-human partnership promises enhanced creativity and insight if used mindfully. Key Insights 🤖 AI as Cognitive Offloading on a New Scale: The video highlights how AI transcends traditional tools by not only storing information but actively processing it—reading, analyzing, and synthesizing complex data. This represents a quantum leap in cognitive offloading and redefines how humans interact with knowledge work. However, this new scale of offloading also means that entire cognitive domains could be ceded to machines if not managed carefully. 🧠 Human Brain’s Efficiency and Its Double-Edged Nature: The brain’s evolutionary drive for efficiency means it naturally seeks shortcuts, which AI facilitates. While this conserves energy and frees up capacity, it also risks deconditioning the very skills—critical thinking, problem-solving, creativity—that define human intellect. The video insightfully frames this not as a moral failing but an inherent biological imperative, underscoring the challenge of balancing convenience with cognitive health. 🔄 Neuroplasticity and Skill Atrophy: The brain’s adaptability means that mental skills are not fixed but require consistent use. The analogy of losing high school language skills encapsulates how disuse leads to weakening neural pathways. The video extends this principle to cognitive skills affected by AI usage, suggesting that passive consumption of AI outputs may cause deterioration in attention span, memory recall, and creative capacity. ⚖️ Balancing AI Use with Cognitive Engagement: The key takeaway is that AI should be used as a partner, not a replacement. The video advocates for intentional habits that preserve human agency, such as questioning AI’s conclusions, synthesizing information independently, and using AI-generated content as a springboard rather than a final product. This perspective redefines digital literacy as a set of critical engagement practices rather than mere tool proficiency. 🏢 Organizational Responsibility in AI Integration: Beyond individual users, organizations must architect workflows that integrate AI collaboratively. This means designing roles and processes that leverage AI’s strengths while preserving human creativity and oversight. The video suggests that doing so can foster a new intellectual era rather than signaling a decline in human ingenuity. This insight points to the broader socio-technical challenge of embedding AI ethically and productively in workplaces. 🌟 Optimistic Vision for Human-AI Synergy: The video paints a hopeful picture where AI liberates humans from mundane tasks, enabling scientists, artists, and other creators to push boundaries and innovate. This vision depends on conscious choices today, highlighting mindfulness and ethical considerations as foundational to harnessing AI’s potential. It positions AI as an “apprentice” that requires human direction, fostering a symbiotic relationship rather than dependency. 🧩 Valuing the Mental Journey: Finally, the video underscores the intrinsic value of mental effort—the struggle, concentration, and creativity involved in problem-solving—as essential to developing expertise and wisdom. These are “not bugs to engineer away” but vital features of human cognition. This insight challenges the prevailing narrative that convenience and automation are unqualified goods, advocating instead for a balanced approach that respects and nurtures the cognitive process.